What is the main benefit of using machine learning in UEBA?

The primary advantage of utilizing machine learning in User and Entity Behavior Analytics (UEBA) is its capability to identify insider threats and compromised accounts effectively. Machine learning algorithms analyze vast amounts of user and entity behavior data to establish baseline patterns of normal activity. Once these normal patterns are established, the system can detect deviations from the baseline that may indicate suspicious behavior, such as insider threats or credential misuse.

This identification process is crucial because it allows organizations to respond swiftly to potential security incidents, thereby reducing the risk of data breaches and ensuring that any malicious activity is addressed promptly. By leveraging machine learning, the UEBA system can continually improve its detection capabilities by learning from new behaviors and adapting over time, making it a powerful tool for enhancing cybersecurity posture.

In contrast, other options focus on different aspects of technology management and security rather than the specific advantages provided by machine learning in the context of UEBA.